Design And Implementation Of Learning Early Warning System Based On Knowledge Structure

Under the guidance of scientific theory,learning early warning is to comprehensively evaluate students' learning behavior,test scores and other external factors according to certain scientific standards,and feedback the evaluation results to the teaching managers and learners in two directions and provide scientific and accurate,Targeted and effective intervention opinions or early warning information.At present,the domestic research field on learning early warning focuses more on the online learning environment or the higher campus environment,and the research on learning early warning in the field of basic education research needs to be strengthened.How to take root in the basic education environment and realize the early warning of course learning is the focus of this study.First,this study summarizes the relevant literature research on learning early warning and cognitive diagnosis.Under the guidance of Bloom's educational target taxonomy and educational measurement theory,around the focus and functional requirements of this study,amodel of learning early warning system based on knowledge structure is proposed and elaborated.Subsequently,the learning and early warning system based on knowledge structure is implemented according to the requirements of functional modules and implementation mechanism,and a brief introduction to its implementation process.Secondly,this study carried out experimental research on the basis of a learning early warning system based on knowledge structure.The experimental results show that the learning early warning system applied to basic education is conducive to the improvement of teaching effects.The experiment selected two parallel classes of students in the second grade of a middle school as subjects.The experimental class introduced a learning early warning system to intervene teaching,and compared with the regular teaching of the class.The experimental class uses the system to collect all the data generated by the measured objects during the learning process,and conducts the mining of association rules that do not have knowledge points.The teachers provide intervention support or scientific teaching guidance to the learners according to the system output,and then in the next stage Test the knowledge of the learners,and compare and analyze the relevant data.To a certain extent,this study fills the gaps in learning early warning in the field of basic education research.It uses association analysis algorithms to mine the information and structure implicit in the data,providing experience support for discovering the association rules of learners who have not mastered knowledge points.